Patient longitudinal data from claims databases provide a lot of valuable insights on patient behaviour and treatment algorithms being followed in practice.
There are quite a few questions that need to be answered after the huge volume of patient data is extracted:
Value Edge has developed a SAS based math engine to summarize and calculate the various parameters on the patient longitudinal data such as duration of brand therapy, duration of class therapy, individual patient compliance at individual drug level, use of drug in various line of therapy taking in consideration the various dosing regimen of the individual drug classes. Value Edge's proprietary solution, Patient Edge provides the necessary answers to all questions.
Value Edge's team takes a very pragmatic approach to do ad-hoc modeling in MS Excel, VBA, Access to offer business solutions to clients. Our clients often have need to build quick tools to do some data management or analytics that does not fall under a specific service line. One example of such a deliverable is given below:
Our client wanted to do a pharmacy stock planning for their key products. The primary questions were:
Value Edge developed an access based tool to do the pharmacy stock planning. The model enabled the client to produce account-specific and targeted stocking recommendations for key trade channel customers, which align with the business dynamics and geographic distribution of retail outlets.
Model and Data Filters
The Launch Stock Plan model provided account-specific stocking recommendations based on data filters that provide a significant level of specificity as to early Rx volume and stocking requirements. Filters employed geographic overlay filters including:
Output for Trade Channel Accounts
The model produced reports that the client provided to their retail accounts to map out sales volume forecasts and stocking volume.